Hardware Engineer

Position: Hardware Application Engineer – Structural Design Employment Type: Full-Time Schedule: Hybrid, 3 days onsite per week About the Opportunity The team at EDGE has partnered with an innovative computer vision company in the Greater Boston area in their search for an experienced Hardware Application Engineer to help design, configure, and deploy the physical hardware systems that support machine vision applications. This is a highly hands‑on role combining industrial cameras, optics, lighting, structural design, edge computing, GPUs, and hardware integration . You'll work with engineering and deployment teams to determine the right hardware configuration for each customer application and help take systems from initial requirements through testing and production deployment. Candidates must be based in the Boston area or willing to relocate and commute to Cambridge at least 3 days per week. What You'll Do Work with engineering and deployment teams to define hardware requirements based on customer applications and manufacturing environments. Design and configure machine vision hardware systems, including cameras, lenses, lighting, mounting structures, enclosures, and supporting components. Evaluate environmental and operational factors such as line speed, part movement, vibration, ambient lighting, available space, and mounting constraints. Recommend and configure industrial cameras, optics, lighting systems, image acquisition hardware, NVIDIA GPUs, edge computing equipment, and networking hardware. Support the structural design and integration of camera mounts, lighting enclosures, protective housings, and other system components. Help test, troubleshoot, and qualify hardware for pilot and production environments. Work with field and deployment teams to diagnose imaging, hardware, calibration, and integration issues. Create hardware configuration documentation, wiring diagrams, bills of materials, and installation/setup guides. Participate in customer site assessments, installations, commissioning, and production validation as needed. Collaborate with cross functional engineering teams to ensure hardware supports reliable computer vision inference. What We're Looking For 5+ years of experience in hardware engineering, systems integration, machine vision, industrial automation, or a related engineering discipline. Hands‑on experience with industrial cameras and camera deployment . Strong understanding of optics, lenses, lighting, imaging sensors, and image acquisition . Experience selecting and configuring cameras from manufacturers such as Basler, FLIR, Allied Vision, Teledyne , or similar. Experience evaluating camera placement, field of view, working distance, resolution, lighting, exposure, and environmental conditions. Experience with hardware integration and structural/mounting considerations for real world deployments. Familiarity with NVIDIA GPUs, edge computing, and hardware used for AI inference . Ability to troubleshoot hardware and imaging issues in manufacturing or industrial environments. Strong communication skills and the ability to work closely with engineering, deployment, and field teams. Preferred Experience Machine vision systems used for automated defect detection or quality inspection. Manufacturing automation or high speed production environments. PLCs, encoders, sensors, triggers, robotics, or industrial networking. GigE Vision, USB3 Vision, GenICam, or similar machine vision interfaces. Camera calibration and image acquisition. Experience with structural design, mechanical mounting, enclosures, or CAD. OpenCV or other image processing/calibration tools. Experience with advanced imaging such as structured lighting, telecentric lenses, polarized imaging, 3D vision, or multispectral imaging. Willingness to travel to customer manufacturing sites when needed. #J-18808-Ljbffr